AWS Machine Learning Blog

Translating documents, spreadsheets, and presentations in Office Open XML format using Amazon Translate

Now you can translate .docx, .xlsx, and .pptx documents using Amazon Translate. Every organization creates documents, spreadsheets, and presentations to communicate and share information with a large group and keep records for posterity. These days, we interact with people who don’t share the same language as ours. The need for translating such documents has become […]

Simplifying application onboarding with Amazon CodeGuru Profiler

Amazon CodeGuru Profiler provides recommendations to help you continuously fine-tune your application’s performance. It does this by collecting runtime performance data from your live applications. It looks for your most expensive lines of code continuously and provides intelligent recommendations. This helps you more easily understand your applications’ runtime behavior so you can optimize their performance, […]

How SNCF Réseau and Olexya migrated a Caffe2 vision pipeline to Managed Spot Training in Amazon SageMaker

This blog post is co-written by guest authors from SNCF and Olexya. Transportation and logistics are fertile ground for machine learning (ML). In this post, we show how the French state-owned railway company Société Nationale des Chemins de fer Français (SNCF) uses ML from AWS with the help of its technology partner Olexya to research, […]

Building a multilingual question and answer bot with Amazon Lex

Updated June 2021 – QnABot now supports voice interaction in multiple languages using Amazon LexV2. You can use Amazon Lex to build a question and answer chatbot. However, if you live in a non-English-speaking country or your business has global reach, you will want a multilingual bot to cater to all your users. This post […]

Enhancing your chatbot experience with web browsing

Chatbots are popping up everywhere. They are qualifying leads, assisting with sales, and automating customer service. However, conversational chatbot experiences have been limited to the space available within the chatbot window. What if these web-based chatbots could provide an interactive experience that expanded beyond the chat window to include relevant web content based on user […]

Processing PDF documents with a human loop using Amazon Textract and Amazon Augmented AI

Businesses across many industries, including financial, medical, legal, and real estate, process a large number of documents for different business operations. Healthcare and life science organizations, for example, need to access data within medical records and forms to fulfill medical claims and streamline administrative processes. Amazon Textract is a machine learning (ML) service that makes […]

Setting up human review of your NLP-based entity recognition models with Amazon SageMaker Ground Truth, Amazon Comprehend, and Amazon A2I

Update Aug 12, 2020 – New features: Amazon Comprehend adds five new languages(Spanish, French, German, Italian and Portuguese) read here. Amazon Comprehend increased the limit of number of entities per custom entity model from 12 to 25 read here. Organizations across industries have a lot of unstructured data that you can evaluate to get entity-based […]

Extracting custom entities from documents with Amazon Textract and Amazon Comprehend

Amazon Textract is a machine learning (ML) service that makes it easy to extract text and data from scanned documents. Textract goes beyond simple optical character recognition (OCR) to identify the contents of fields in forms and information stored in tables. This allows you to use Amazon Textract to instantly “read” virtually any type of […]

Increasing engagement with personalized online sports content

This is a guest post by Mark Wood at Pulselive. In their own words, “Pulselive, based out of the UK, is the proud digital partner to some of the biggest names in sports.” At Pulselive, we create experiences sports fans can’t live without; whether that’s the official Cricket World Cup website or the English Premier […]

Deploying custom models built with Gluon and Apache MXNet on Amazon SageMaker

When you build models with the Apache MXNet deep learning framework, you can take advantage of the expansive model zoo provided by GluonCV to quickly train state-of-the-art computer vision algorithms for image and video processing. A typical development environment for training consists of a Jupyter notebook hosted on a compute instance configured by the operating […]